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He, Ran

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11 papers 2024–2026

Supervised Fine-Tuning for Reasoning Large Language Models: A Survey

Yu, Yongcan, Guo, Kuangpu, Liang, Jian, He, Lingxiao, Wang, Meng, He, Ran
2026-01 Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing

AgentHallu: Benchmarking Automated Hallucination Attribution of LLM-based Agents

Liu, Xuannan, Yang, Xiao, Li, Zekun, Li, Pei Pei, He, Ran
2026-01 Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing

Do MLLMs Really Understand Space? A Mathematical Spatial Reasoning Evaluation

Lu, Shuo, Cheng, Jianjie, Xu, Yinuo, Yu, Yongcan, Sheng, Lijun, Wang, Peijie
+8 more show fewer
Jiang, Siru, Hu, Yongguan, He, Lingxiao, Wang, Meng, Xie, Qianlong, Wang, Xingxing, He, Ran, Liang, Jian
2026-01 Findings of the Association for Computational Linguistics: EMNLP 2026

When Not to Imitate: Boundary-Aware Skill Memory for Reliable Tool-Use LLM Agents

Lin, Zihan, Chen, Zhenyu, Wei, Jiawen, Wang, Xiaohan, Cao, Jie, Chai, Jiajun
+3 more show fewer
Lin, Wei, Yin, Guojun, He, Ran
2026-01 Findings of the Association for Computational Linguistics: EMNLP 2026

CE-GAD: Curriculum-Efficient On-Policy Adversarial Distillation of Large Language Models

Zhu, Wenhui, Sang, Hejian, Chen, Xiwen, Wang, Zhipeng, Mohajer Hamidi, Shayan, Yu, Han
+9 more show fewer
Wang, Jingjing, Xu, Yuanda, Dong, Xuanzhao, Zhou, Zhengze, He, Ran, Markovic-Voronov, Jelena, Behdin, Kayhan, Ghosh, Sayan, Geramifard, Alborz
2026-01 Findings of the Association for Computational Linguistics: EMNLP 2026

Beyond GRPO and On-Policy Distillation: An Empirical Sparse-to-Dense Reward Principle for Language-Model Post-Training

Xu, Yuanda, Sang, Hejian, Zhou, Zhengze, He, Ran, Wang, Zhipeng, Geramifard, Alborz
2026-01 Findings of the Association for Computational Linguistics: EMNLP 2026

DeVAn: Dense Video Annotation for Video-Language Models

Liu, Tingkai, Tao, Yunzhe, Liu, Haogeng, Fang, Qihang, Zhou, Ding, Huang, Huaibo
+2 more show fewer
He, Ran, Yang, Hongxia
2024-01 Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

InfiMM: Advancing Multimodal Understanding with an Open-Sourced Visual Language Model

Liu, Haogeng, You, Quanzeng, Wang, Yiqi, Han, Xiaotian, Zhai, Bohan, Liu, Yongfei
+6 more show fewer
Chen, Wentao, Jian, Yiren, Tao, Yunzhe, Yuan, Jianbo, He, Ran, Yang, Hongxia
2024-01 Findings of the Association for Computational Linguistics: ACL 2024

InfiMM-WebMath-40B: Advancing Multimodal Pre-Training for Enhanced Mathematical Reasoning

Han, Xiaotian, Jian, Yiren, Hu, Xuefeng, Liu, Haogeng, Wang, Yiqi, Fan, Qihang
+5 more show fewer
Ai, Yuang, Huang, Huaibo, He, Ran, Yang, Zhenheng, You, Quanzeng
2025-01 Findings of the Association for Computational Linguistics: EMNLP 2025

What If Consensus Lies? Selective-Complementary Reinforcement Learning at Test Time

Yan, Dong, Liang, Jian, Wang, Yanbo, Lu, Shuo, He, Ran, Tan, Tieniu
2026-01 Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Understanding and Mitigating Spurious Signal Amplification in Test-Time Reinforcement Learning for Math Reasoning

Yu, Yongcan, He, Lingxiao, Liang, Jian, Guo, Kuangpu, Wang, Meng, Xie, Qianlong
+2 more show fewer
Wang, Xingxing, He, Ran
2026-01 Findings of the Association for Computational Linguistics: ACL 2026